| 1. |
- Kanai, M, et al.
(författare)
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- 2023
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swepub:Mat__t
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| 2. |
- Niemi, MEK, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 3. |
- Namkoong, H, et al.
(författare)
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DOCK2 is involved in the host genetics and biology of severe COVID-19
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 609:7928, s. 754-
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Tidskriftsartikel (refereegranskat)abstract
- Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1–5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.
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| 4. |
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| 5. |
- Wang, QBS, et al.
(författare)
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The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force
- 2022
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1, s. 4830-
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Tidskriftsartikel (refereegranskat)abstract
- Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection.
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| 11. |
- Morita, Y, et al.
(författare)
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ASXL1 mutations with serum EPO levels predict poor response to darbepoetin alfa in lower-risk MDS: W-JHS MDS01 trial
- 2022
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Ingår i: International journal of hematology. - : Springer Science and Business Media LLC. - 1865-3774 .- 0925-5710. ; 116:5, s. 659-668
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Tidskriftsartikel (refereegranskat)abstract
- Darbepoetin alfa (DA) is used to treat anemia in lower-risk (IPSS low or int-1) myelodysplastic syndromes (MDS). However, whether mutations can predict the effectiveness of DA has not been examined. The present study aimed to determine predictive gene mutations. The primary endpoint was a correlation between the presence of highly frequent (≥ 10%) mutations and hematological improvement-erythroid according to IWG criteria 2006 by DA (240 μg/week) until week 16. The study included 79 patients (age 29–90, median 77.0 years; 52 [65.8%] male). Frequently (≥ 10%) mutated genes were SF3B1 (24 cases, 30.4%), TET2 (20, 25.3%), SRSF2 (10, 12.7%), ASXL1 (9, 11.4%), and DNMT3A (8, 10.1%). Overall response rate to DA was 70.9%. Multivariable analysis including baseline erythropoietin levels and red blood cell transfusion volumes as variables revealed that erythropoietin levels and mutations of ASXL1 gene were significantly associated with worse response (odds ratio 0.146, 95% confidence interval 0.042–0.503; p = 0.0023, odds ratio 0.175, 95% confidence interval 0.033–0.928; p = 0.0406, respectively). This study indicated that anemic patients who have higher erythropoietin levels and harbor ASXL1 gene mutations may respond poorly to DA. Alternative strategies are needed for the treatment of anemia in this population. Trial registration number and date of registration: UMIN000022185 and 09/05/2016.
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| 12. |
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| 13. |
- Morita, Yuki, et al.
(författare)
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Applying Bayesian optimization with Gaussian process regression to computational fluid dynamics problems
- 2022
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Ingår i: Journal of Computational Physics. - : Elsevier BV. - 0021-9991 .- 1090-2716. ; 449
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Tidskriftsartikel (refereegranskat)abstract
- Bayesian optimization (BO) based on Gaussian process regression (GPR) is applied to different CFD (computational fluid dynamics) problems which can be of practical relevance. The problems are i) shape optimization in a lid-driven cavity to minimize or maximize the energy dissipation, ii) shape optimization of the wall of a channel flow in order to obtain a desired pressure-gradient distribution along the edge of the turbulent boundary layer formed on the other wall, and finally, iii) optimization of the controlling parameters of a spoiler-ice model to attain the aerodynamic characteristics of the airfoil with an actual surface ice. The diversity of the optimization problems, independence of the optimization approach from any adjoint information, the ease of employing different CFD solvers in the optimization loop, and more importantly, the relatively small number of the required flow simulations reveal the flexibility, efficiency, and versatility of the BO-GPR approach in CFD applications. It is shown that to ensure finding the global optimum of the design parameters of the size up to 8, less than 90 executions of the CFD solvers are needed. Furthermore, it is observed that the number of flow simulations does not significantly increase with the number of design parameters. The associated computational cost of these simulations can be affordable for many optimization cases with practical relevance.
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| 14. |
- Rezaeiravesh, Saleh, et al.
(författare)
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Bayesian Optimisation with Gaussian Process Regression Applied to Fluid Problems
- 2021
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Ingår i: Progress in Turbulence IX. - Cham : Springer Science and Business Media Deutschland GmbH. ; , s. 137-143
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Konferensbidrag (refereegranskat)abstract
- Bayesian optimisation based on Gaussian process regression (GPR) is an efficient gradient-free algorithm widely used in various fields of data sciences to find global optima. Based on a recent study by the authors, Bayesian optimisation is shown to be applicable to optimisation problems based on simulations of different fluid flows. Examples range from academic to more industrially-relevant cases. As a main conclusion, the number of flow simulations required in Bayesian optimisation was found not to exponentially grow with the dimensionality of the design parameters (hence, no curse of dimensionality). Here, the Bayesian optimisation method is outlined and its application to the shape optimisation of a two-dimensional lid-driven cavity flow is detailed.
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